:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Shen, Yihang, Kingsford, Carl
Format:	Preprint
Published:	2021
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2109.09264
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

High Dimensional Bayesian Optimization using Lasso Variable Selection
by: Hoang, Vu Viet, et al.
Published: (2025)

Diffusion-Driven High-Dimensional Variable Selection
by: Wang, Minjie, et al.
Published: (2025)

Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization
by: Namura, Nobuo, et al.
Published: (2024)

Leveraging Axis-Aligned Subspaces for High-Dimensional Bayesian Optimization with Group Testing
by: Hellsten, Erik, et al.
Published: (2025)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
by: Tran-The, Hung, et al.
Published: (2019)

CodonMoE: DNA Language Models for mRNA Analyses
by: Du, Shiyi, et al.
Published: (2025)

Understanding High-Dimensional Bayesian Optimization
by: Papenmeier, Leonard, et al.
Published: (2025)

High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces
by: Nguyen, Quoc-Anh Hoang, et al.
Published: (2024)

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation
by: Li, Jiayi, et al.
Published: (2026)

An Adaptive Dropout Approach for High-Dimensional Bayesian Optimization
by: Huang, Jundi, et al.
Published: (2025)

Vanilla Bayesian Optimization Performs Great in High Dimensions
by: Hvarfner, Carl, et al.
Published: (2024)

scMamba: A Scalable Foundation Model for Single-Cell Multi-Omics Integration Beyond Highly Variable Feature Selection
by: Yuan, Zhen, et al.
Published: (2025)

Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization
by: Zhao, Jiayu, et al.
Published: (2023)

We Still Don't Understand High-Dimensional Bayesian Optimization
by: Doumont, Colin, et al.
Published: (2025)

High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
by: Yin, Yuxuan, et al.
Published: (2023)

Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
by: Zhan, Dawei
Published: (2024)

Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
by: Santoni, Maria Laura, et al.
Published: (2023)

Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
by: Wei, Yunyue, et al.
Published: (2024)

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
by: Papenmeier, Leonard, et al.
Published: (2023)

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
by: Bardou, Anthony, et al.
Published: (2023)

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
by: Chen, Yihang, et al.
Published: (2024)

Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing
by: Guo, Wanru, et al.
Published: (2026)

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
by: Xu, Zhitong, et al.
Published: (2024)

Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approach
by: Li, Wenxuan, et al.
Published: (2024)

High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings
by: Priem, Rémy, et al.
Published: (2025)

Self-Correcting Bayesian Optimization through Bayesian Active Learning
by: Hvarfner, Carl, et al.
Published: (2023)

BO4Mob: Bayesian Optimization Benchmarks for High-Dimensional Urban Mobility Problem
by: Ryu, Seunghee, et al.
Published: (2025)

Learning Relevant Contextual Variables Within Bayesian Optimization
by: Martinelli, Julien, et al.
Published: (2023)

A General Framework for User-Guided Bayesian Optimization
by: Hvarfner, Carl, et al.
Published: (2023)

Informed Initialization for Bayesian Optimization and Active Learning
by: Hvarfner, Carl, et al.
Published: (2025)

Learn to Explore: Meta NAS via Bayesian Optimization Guided Graph Generation
by: Sun, Zijun, et al.
Published: (2025)

Sequential Reservoir Computing for Efficient High-Dimensional Spatiotemporal Forecasting
by: Asanjan, Ata Akbari, et al.
Published: (2026)

Efficient Malware Detection with Optimized Learning on High-Dimensional Features
by: Choudhary, Aditya, et al.
Published: (2025)

From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
by: Xie, Zikai, et al.
Published: (2025)

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
by: Cheon, Mujin, et al.
Published: (2024)

Categorical Optimization with Bayesian Anchored Latent Trust Regions for Structural Design under High-Dimensional Uncertainty
by: Liang, Zhangyong, et al.
Published: (2026)

High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020)

High dimensional Bayesian Optimization via Condensing-Expansion Projection
by: Lu, Jiaming, et al.
Published: (2024)

Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs
by: Hoang, Vu Viet, et al.
Published: (2024)

Differentially Private High-dimensional Variable Selection via Integer Programming
by: Prastakos, Petros, et al.
Published: (2025)